1. Field of the Invention
The present invention relates to a computer system. More particularly, the present invention relates to a method, apparatus and program storage device for providing data path optimization for redundant data paths.
2. Description of Related Art
In recent years, installed disk storage capacity has seen an almost exponential growth at customer sites. This exponential growth has been coupled with the movement away from direct attached storage to networked storage, be it either storage area network (SAN) or network-attached storage (NAS). Also the movement has resulted in an ever-increasing complexity of the storage management environment.
Implementing a successful application to resolve the complexity of the storage environment is as much an art as it is a science. Companies are increasingly struggling with applications that require extraordinary resources. In some cases, these resources require expensive components plus increased fees for software licensing.
Storage designers and application developers need to address multiple concerns when developing storage solutions. A few of those concerns include multiple data paths, failover, transaction and batch elapsed time, the amount of CPU required to sustain transaction and batch processes, and concurrency. These metrics quantify a storage network and its database's performance. To ensure good performance, designers and developers should incorporate an understanding of the importance of each of these metrics into all of their applications.
Multiple, or redundant, data paths between, for example, a server and a storage subsystem is extremely important for optimum system performance and availability of the storage subsystem. If a failure occurs in the data path between a system server and a remote data storage subsystem, automatic switching of the input/output (I/O) to another path is essential for performance and availability of the system overall.
To improve the performance and availability of data access, from a host to remote data storage subsystems for example, the host machine must be able to access remote data storage subsystems through multiple paths thereby increasing the data access throughput and improve availability, and providing failover protection. A database optimizer works to find the best access path to access data through the multiple paths. The optimizer will figure out the shortest path to the data and determine the least expensive way to complete the work even in the event of a single or multiple path failure. In addition, an I/O workload can be spread over multiple active paths by the optimizer, which can eliminate bottlenecks that occur when many I/O operations are directed to a device, such as a common disk device, across the same path.
An optimizer may also help to reduce I/O transmission time. When tables and indexes to physical devices are designed properly, programs can update a database with information that enables the optimizer to take the minimum path. Finding the best path helps reduce I/O and CPU expenditure and fulfills application requests for data as quickly and as efficiently as possible.
However, in host-to-remote data storage subsystems, an operating system (OS) sees separate bus paths to the same device and the OS is unaware that the separate bus paths are in fact connected to the same device. For example, multiple bus paths may be connected to the same storage subsystem. Hence, when a path fails, a “Write Delay Error” would be generated for that path instead of failing over to another path.
Moreover, current optimization products do not support access to remote devices, such as remote data storage subsystems, through multiple paths on all platforms. For example, one product's algorithm for remote storage through multiple paths may work well on a UNIX™ platform, but not be compatible with an operating system using Plus and Play, such as on a Windows™ platform. On these platforms, which are not fully Plug and Play compatible, write errors are encountered.
It can be seen that there is a need to provide data path optimization for redundant data paths to allow access to devices through multiple paths on multiple platforms.
It can also be seen that there is a need for data path optimization that supports multi-path device operation with Plug and Play compatibility.